Multilevel least-change Newton-like methods for equality constrained optimization problems

This paper deals with the application of multilevel least-change Newton-like methods for solving twice continuously differentiable equality constrained optimization problems. We define multilevel partial-inverse least-change updates, multilevel least-change Newton-like methods without derivatives and multilevel projections of fragments of the matrix for Newton-like methods without derivatives. Local andq-superlinear convergence of these methods is proved. The theorems here also imply local andq-superlinear convergence of many standard Newton-like methods for nonconstrained and equality constraine optimization problems.